The modeling issues inherent in testing and evaluating knowledge-based systems

摘要

Computer science has always been concerned with the problem of organizing and representing knowledge to make it effectively computable. Expert systems or knowledge-based systems (KBSs)1 are not dramatic departures from other computer programs. Rather, they bring together and extend a number of the innovations and concerns that characterize modern computer science. However, like the classes of special-application programs before them or like programs written in new languages, they avoid some of the errors with which we are familiar and create new ones that we need to discover. Part of our ability to specify and test such programs adequately depends upon our ability to discover as quickly as possible (a) the kinds of errors and problems that their new constructs, goals, and processing qualities introduce and (b) the methods, analyses, and tests that will allow one to identify these errors and to fix them.